In another internship we are building a prototype of smart trashcan with necessary sensors to check if it needs to be emptied. When it is time to be emptied it should place itself in a central position for the cleaning personnel to handle.
Description of the assignment
The aim of this internship is to build the office in a gaming environment (Unity) and then use reinforcement learning to make the autonomous drive to the central position where the cleaning personnel can pick it up.
Goals
The autonomous drive itself should be challenging enough to cope with moving objects and displacement of objects, such as chairs that get in its trajectory or a person walking by.
What you will gain
Learn how to design an end-to-end data processing pipeline
AND put this in production
Gain knowledge about steam processing
Gain knowledge and experience in machine learning
You will get to know Hadoop
You will gain experience in powerful visualization libraries such as D3.js
That lovely feeling you get knowing your design will be effectively used in production
What you need
You have a shown interest in a challenging but instructive assignment
You’d like to explore Machine Learning and stream processing techniques
Using Spark, Python or Scala does not scare you at all
You know what ReactJS is, or are eager to learn
You like to learn about data visualization
You like to learn a heck of a lot on a relatively short period of time
Technologies you'll be using
Reinforcement learning
Unity
Tensorflow
Python
Location of your assignment
Veldkant 33B, 2550 Kontich
Your mentor
Kevin Smeyers – Technical lead machine learning ToThePoint